JayDevs - Software Development Company

How outsourcing has helped Apple, Google, GitHub and other IT companies become who they are 👇

Follow the link to find out:

- What are the common reasons for companies to outsource;
- Why did the above companies decide to do that;
- And what lessons we can learn from their experiences.

Why Do Companies Outsource? Lessons Learned and Software Outsourcing Examples - JayDevs Outsourcing is a common practice in IT industry. So let's find out why do companies choose to outsource work with 10 fascinating outsourcing examples.

Liver cancer is one of the leading causes of cancer deaths worldwide, with more than 800,000 people diagnosed each year.

Researchers from Johns Hopkins Kimmel Cancer Center have developed an AI-based test that can help doctors detect this type of cancer.

The blood testing technology, known as DNA evaluation of fragments for early interception (DELFI), earlier allowed researchers to successfully classify lung cancer in 2021. Now, scientists have used this technology to detect liver cancer.

DELFI works by measuring the amount and size of cell-free DNA present in the blood from different parts across the genome. Cancer cells release DNA fragments into the blood when they die, giving an opportunity to detect tumors at early stages and without invasive tests.

The recent study evaluated samples from 724 people from the U.S., the European Union and Hong Kong to detect hepatocellular cancer, the most common type of primary liver cancer.

The study involved people who either had liver cancer or were at average or high risk of developing the disease. DELFI achieved 88% sensitivity and 98% specificity in the average-risk group, and 85% sensitivity and 80% specificity in the high-risk cohort.

Assistant professor of medicine at the Johns Hopkins University School of Medicine, Amy Kim, M.D., outlined the potential implications of the study.

“Currently, less than 20% of the high-risk population get screened for liver cancer due to accessibility and suboptimal test performance. This new blood test can double the number of liver cancer cases detected, compared to the standard blood test available, and increase early cancer detection.”

Every year, AI is being implemented more and more into the healthcare industry. Jaydevs is honored to be one of the companies taking a part in this movement.

Recently, we participated in a similar medtech project. We have developed a web application and integrated an AI algorithm into it to detect various diseases (cancer, skin diseases, etc.).

So, if you have ideas on how to implement AI in healthcare, contact us. We will be glad to help you with the implementation of your idea -https://jaydevs.com/

3 easy steps to provide specific and actionable feedback to software developers with the SBI framework 👇

Sometimes, it’s hard to stay objective when giving feedback. We all have our sense of right and wrong, and often jump to conclusions based on our own assumptions about people's behavior. While this may be true, this type of feedback is generally unhelpful.

The Center for Creative Leadership created an SBI framework that helps you remove judgment out of your feedback and make it more clear, so the recipient becomes less defensive about it. The framework consists of 3 simple steps.

01. Situation.

When you’re giving feedback, first define where and when the situation occurred. This makes the feedback more specific, so developers can easily relate to it.

02. Behavior.

Next, describe the behavior without judgments and without assuming you already know what they have in mind. This is the most challenging part of the process as you must communicate only the behaviors that you observed directly.

For example, if you observed that a developer made a mistake, you should not assume that he/she prepared poorly. You should simply comment that the mistake was made, ideally note what the mistake was.

By being objective and stating the facts, you lower high emotions that can occur when feedback is given. This also helps you avoid making assumptions that could upset the employee and damage your cooperation.

03. Impact.

Describe your thinking or feeling about the behavior. Keep in mind how developers’ actions have affected the process. Focus on information that can be measurable.

Once you’ve delivered your feedback, encourage developers to think about the situation and understand the impact of their behavior. Allow them time to absorb what you have said, and then go over specific actions that will help them to improve.

When you structure feedback this way, your developers will understand precisely what you are commenting on, and why. This could be a great step for their further growth.

Like the post if it was helpful and share your ideas on providing effective feedback!

Copilot's potential for business, initial developer reactions, and who it is not suitable for 👇

An AI "pair programmer," GitHub Copilot made its debut in June 2022 following a year of technical previews.

It is based on the OpenAI Codex and assists developers by suggesting the next line of code, complete functions or more complex algorithms when they might be suitable. For individuals, the service costs $10 per user per month or $100 per user per year.

GitHub’s Copilot has proven to be popular with coders. Among core advantages they highlight:

- Less time spent browsing for solutions on the internet;
- Smarter code completion than typical IDEs offer;
- And tiny boosts with contextualized solutions;

All of the above results in a greater focus on the big picture, architecture, and integration.

On the more qualitative front, a majority of Copilot users reported they were less frustrated with coding and more satisfied with their job at 59% and 60%, respectively (according to internal GitHub research).

Although, the majority of developers said Copilot can speed up daily work, they also said it won’t do the job for you. At the end of the day, developers are still responsible for delivering quality code, even if they use AI assistance.

❗️ The GitHub FAQ states that “Inexperienced developers may struggle to use Copilot to effectively generate code, as their lack of experience might inhibit their capability to effectively review and edit suggestions made by Copilot.”

A version for business will be launching soon. Once launched, companies will be able to purchase and manage seat licenses of the tool for their teams of employees, helping them significantly expand their use of AI.

Alongside with expansion, GitHub is experimenting with a new voice-based interaction system for its Copilot. “Hey, GitHub!” will allow programmers to code with just their voice and no keyboard, just like how you’d speak to Siri, Alexa, or Google Assistant.

The feature is currently being tested by the GitHub Next research team. It eventually could speed up the programming process even more, as using a voice is faster than using a mouse and keyboard. It would also make coding more accessible to those who can’t use the standard manual tools.

Have you had the opportunity to test Copilot? How do you assess the prospects of using voice-assistants in software development? Share your thoughts in the comments.